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performance evaluation of multithreaded sparse matrix-vector multiplication using openmp
Liu Shengfei; Zhang Yunquan; Sun Xiangzheng; Qiu RongRong
2009
Conference Name11th IEEE International Conference on High Performance Computing and Communications
Source2009 11th IEEE International Conference on High Performance Computing and Communications, HPCC 2009
Conference DateJUN 25-27,
Conference PlaceSeoul, SOUTH KOREA
Publish Place345 E 47TH ST, NEW YORK, NY 10017 USA
PublisherHPCC: 2009 11TH IEEE INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING AND COMMUNICATIONS
ISBN978-1-4244-4600-1
DepartmentLiu, Shengfei; Zhang, Yunquan; Sun, Xiangzheng Chinese Acad Sci, Inst Software, Beijing 100864, Peoples R China.
English AbstractSparse matrix-vector multiplication is an important computational kernel in scientific applications. However, it performs poorly on modern processors because of a low compute-to-memory ratio and its irregular memory access patterns. This paper discusses the implementations of sparse matrix-vector algorithm using OpenMP to execute iterative methods on the Dawning S4800A1. Two storage formats (CSR and BCSR) for sparse matrices and three scheduling schemes (static, dynamic and guided) provided by the standard OpenMP are evaluated We also compared these three schemes with non-zero scheduling, where each thread is assigned approximately the same number of non-zero elements. Experimental data shows that, the non-zero scheduling can provide the best performance in most cases. The current implementation provides satisfactory scalability for most of matrices. However, we only get a limited speedup for some large matrices that contain millions of non-zero elements.
KeywordDawning S4800a1 Openmp Compute-to-memory Ratio Irregular Memory Access Patterns Iterative Methods Multithreaded Sparse Matrix-vector Multiplication Nonzero Scheduling Performance Evaluation Application Program Interfaces Matrix Multiplication Multi-threading Scheduling Shared Memory Systems Software Performance Evaluation Sparse Matrices Vectors
SponsorshipIEEE Comp Soc, IEEE
Content Type会议论文
URIhttp://ir.iscas.ac.cn/handle/311060/8288
Collection并行软件与计算科学实验室 
Recommended Citation
GB/T 7714
Liu Shengfei,Zhang Yunquan,Sun Xiangzheng,et al. performance evaluation of multithreaded sparse matrix-vector multiplication using openmp[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:HPCC: 2009 11TH IEEE INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING AND COMMUNICATIONS,2009.
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